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Back‐end‐of‐line SiC‐based memristor for resistive memory and artificial synapse
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Kapur, Omesh, Guo, Dongkai, Reynolds, Jamie, Han, Yisong, Beanland, Richard, Jiang, Liudi, de Groot, C. H. (Kees) and Huang, Ruomeng (2022) Back‐end‐of‐line SiC‐based memristor for resistive memory and artificial synapse. Advanced Electronic Materials . 2200312. doi:10.1002/aelm.202200312 ISSN 2199-160X.
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WRAP-Back‐end‐of‐line-SiC‐memristor-resistive-artificial-synapse-2022.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (2314Kb) | Preview |
Official URL: https://doi.org/10.1002/aelm.202200312
Abstract
Two‐terminal memristor has emerged as one of the most promising neuromorphic artificial electronic devices for their structural resemblance to biological synapses and ability to emulate many synaptic functions. In this work, a memristor based on the back‐end‐of‐line (BEOL) material silicon carbide (SiC) is developed. The thin film memristors demonstrate excellent binary resistive switching with compliance‐free and self‐rectifying characteristics which are advantageous for the implementation of high‐density 3D crossbar memory architectures. The conductance of this SiC‐based memristor can be modulated gradually through the application of both DC and AC signals. This behavior is demonstrated to further emulate several vital synaptic functions including paired‐pulse facilitation (PPF), post‐tetanic potentiation (PTP), short‐term potentiation (STP), and spike‐rate‐dependent plasticity (SRDP). The synaptic function of learning‐forgetting‐relearning processes is successfully emulated and demonstrated using a 3 × 3 artificial synapse array. This work presents an important advance in SiC‐based memristor and its application in both memory and neuromorphic computing.
| Item Type: | Journal Article | |||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Physics | |||||||||
| SWORD Depositor: | Library Publications Router | |||||||||
| Library of Congress Subject Headings (LCSH): | Memristors, Silicon-carbide thin films, Nonvolatile random-access memory, Neuromorphics | |||||||||
| Journal or Publication Title: | Advanced Electronic Materials | |||||||||
| Publisher: | Wiley-Blackwell Publishing Ltd. | |||||||||
| ISSN: | 2199-160X | |||||||||
| Official Date: | 2022 | |||||||||
| Dates: |
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| Article Number: | 2200312 | |||||||||
| DOI: | 10.1002/aelm.202200312 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Reuse Statement (publisher, data, author rights): | ** Article version: VoR ** From Wiley via Jisc Publications Router ** History: received 20-03-2022; rev-recd 03-05-2022; pub-electronic 01-06-2022. ** Licence for VoR version of this article: http://creativecommons.org/licenses/by/4.0/ | |||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||
| Date of first compliant deposit: | 27 June 2022 | |||||||||
| Date of first compliant Open Access: | 27 June 2022 | |||||||||
| RIOXX Funder/Project Grant: |
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